Error in insight::export_table(x = formatted_table, digits = digits, format = "markdown", : unused argument (layout = "vertical")
For interpretation of performance metrics, please refer to this documentation.
| Parameter | Coefficient | SE | 95% CI | t(60) | p |
|---|---|---|---|---|---|
| (Intercept) | -0.53 | 2.66 | (-5.86, 4.79) | -0.20 | 0.842 |
| reference | 0.49 | 0.11 | (0.27, 0.71) | 4.48 | < .001 |
To find out more about table summary options, please refer to this documentation.
| reference | Predicted | SE | CI_low | CI_high |
|---|---|---|---|---|
| 13.66 | 6.15 | 1.25 | 3.65 | 8.65 |
| 16.58 | 7.58 | 0.98 | 5.62 | 9.54 |
| 19.50 | 9.01 | 0.75 | 7.50 | 10.51 |
| 22.42 | 10.44 | 0.61 | 9.22 | 11.66 |
| 25.34 | 11.87 | 0.62 | 10.63 | 13.10 |
| 28.26 | 13.29 | 0.77 | 11.75 | 14.84 |
| 31.18 | 14.72 | 1.01 | 12.71 | 16.73 |
| 34.10 | 16.15 | 1.28 | 13.60 | 18.71 |
| 37.02 | 17.58 | 1.57 | 14.45 | 20.71 |
| 39.94 | 19.01 | 1.87 | 15.28 | 22.74 |
Variable predicted: low_cost
Predictors modulated: reference
We fitted a linear model (estimated using OLS) to predict low_cost with reference (formula: low_cost ~ reference). The model explains a statistically significant and moderate proportion of variance (R2 = 0.25, F(1, 60) = 20.07, p < .001, adj. R2 = 0.24). The model’s intercept, corresponding to reference = 0, is at -0.53 (95% CI (-5.86, 4.79), t(60) = -0.20, p = 0.842). Within this model:
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using the Wald approximation. The model explains a statistically significant and moderate proportion of variance (R2 = 0.25, F(1, 60) = 20.07, p < .001, adj. R2 = 0.24)
---
title: "Regression model summary from `{easystats}`"
output:
flexdashboard::flex_dashboard:
theme:
version: 4
# bg: "#101010"
# fg: "#FDF7F7"
primary: "#0054AD"
base_font:
google: Prompt
code_font:
google: JetBrains Mono
params:
model: model
parameters_args: parameters_args
performance_args: performance_args
---
```{r setup, include=FALSE}
library(flexdashboard)
library(easystats)
# Since not all regression model are supported across all packages, make the
# dashboard chunks more fault-tolerant. E.g. a model might be supported in
# `{parameters}`, but not in `{report}`.
#
# For this reason, `error = TRUE`
knitr::opts_chunk$set(
error = TRUE,
out.width = "100%"
)
```
```{r}
# Get user-specified model data
model <- params$model
# Is it supported by `{easystats}`? Skip evaluation of the following chunks if not.
is_supported <- insight::is_model_supported(model)
if (!is_supported) {
unsupported_message <- sprintf(
"Unfortunately, objects of class '%s' are not yet supported in {easystats}.\n
For a list of supported models, see `insight::supported_models()`.",
class(model)[1]
)
}
```
Model fit
=====================================
Column {data-width=700}
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### Assumption checks
```{r check-model, eval=is_supported, fig.height=10, fig.width=10}
check_model(model)
```
```{r, eval=!is_supported}
cat(unsupported_message)
```
Column {data-width=300}
-----------------------------------------------------------------------
### Indices of model fit
```{r, eval=is_supported}
# `{performance}`
performance_args <- c(list(model), params$performance_args)
table_performance <- do.call(performance::performance, performance_args)
print_md(table_performance, layout = "vertical", caption = NULL)
```
```{r, eval=!is_supported}
cat(unsupported_message)
```
For interpretation of performance metrics, please refer to this documentation.
Parameter estimates
=====================================
Column {data-width=550}
-----------------------------------------------------------------------
### Plot
```{r dot-whisker, eval=is_supported}
# `{parameters}`
parameters_args <- c(list(model), params$parameters_args)
table_parameters <- do.call(parameters::parameters, parameters_args)
plot(table_parameters)
```
```{r, eval=!is_supported}
cat(unsupported_message)
```
Column {data-width=450}
-----------------------------------------------------------------------
### Tabular summary
```{r, eval=is_supported}
print_md(table_parameters, caption = NULL)
```
```{r, eval=!is_supported}
cat(unsupported_message)
```
To find out more about table summary options, please refer to this documentation.
Predicted Values
=====================================
Column {data-width=600}
-----------------------------------------------------------------------
### Plot
```{r expected-values, eval=is_supported, fig.height=10, fig.width=10}
# `{modelbased}`
int_terms <- find_interactions(model, component = "conditional", flatten = TRUE)
con_terms <- find_variables(model)$conditional
if (is.null(int_terms)) {
model_terms <- con_terms
} else {
model_terms <- clean_names(int_terms)
int_terms <- unique(unlist(strsplit(clean_names(int_terms), ":", fixed = TRUE)))
model_terms <- c(model_terms, setdiff(con_terms, int_terms))
}
text_modelbased <- lapply(unique(model_terms), function(i) {
grid <- get_datagrid(model, at = i)
estimate_expectation(model, data = grid)
})
ggplot2::theme_set(theme_modern())
# all_plots <- lapply(text_modelbased, function(i) {
# out <- do.call(visualisation_recipe, c(list(i), modelbased_args))
# plot(out) + ggplot2::ggtitle("")
# })
all_plots <- lapply(text_modelbased, function(i) {
out <- visualisation_recipe(i, show_data = "none")
plot(out) + ggplot2::ggtitle("")
})
see::plots(all_plots, n_columns = round(sqrt(length(text_modelbased))))
```
```{r, eval=!is_supported}
cat(unsupported_message)
```
Column {data-width=400}
-----------------------------------------------------------------------
### Tabular summary
```{r, eval=is_supported, results="asis"}
for (i in text_modelbased) {
tmp <- print_md(i)
tmp <- gsub("Variable predicted", "\nVariable predicted", tmp)
tmp <- gsub("Predictors modulated", "\nPredictors modulated", tmp)
tmp <- gsub("Predictors controlled", "\nPredictors controlled", tmp)
print(tmp)
}
```
```{r, eval=!is_supported}
cat(unsupported_message)
```
Text reports
=====================================
Column {data-width=500}
-----------------------------------------------------------------------
### Textual summary
```{r, eval=is_supported, results='asis', collapse=TRUE}
# `{report}`
text_report <- report(model)
text_report_performance <- report_performance(model)
gsub("]", ")", gsub("[", "(", text_report, fixed = TRUE), fixed = TRUE)
cat("\n")
gsub("]", ")", gsub("[", "(", text_report_performance, fixed = TRUE), fixed = TRUE)
```
```{r, eval=!is_supported}
cat(unsupported_message)
```
Column {data-width=500}
-----------------------------------------------------------------------